Over the last few years, unprecedented computational resources have been developed, such as the BLUE GENE™ family of computers from the International Business Machines Corporation. See N. R. Adiga et al., “An Overview of the Blue Gene/L Supercomputer,” Proceedings of the ACM/IEEE Supercomputing 2002 Conference (SC'02), November 2002, the disclosure of which is incorporated by reference herein. These resources may be used to attack, among other issues, grand challenge life sciences problems such as advancing the understanding of biologically important processes, in particular, the mechanisms behind protein folding.
In order to address this goal, attention has been directed to creating a classical molecular dynamics software package for long-time and large-scale molecular simulations. See F. Allen et al., “Blue Gene: A Vision for Protein Science Using a Petaflop Supercomputer,” IBM Systems Journal, vol. 40, no. 2, pp. 310-327, 2001, the disclosure of which is incorporated by reference herein.
Classical molecular dynamics is predominantly an n-body problem. An n-body problem may be defined as the problem of finding, given the initial positions, masses, and velocities of n bodies, their subsequent motions as determined by classical mechanics. An n-body problem, for example molecular dynamics (MD), proceeds as a sequence of simulation time steps. At each time step, forces on particles, in MD atoms, are computed; and then the equations of motion are integrated to update the velocities and positions of the particles. In order to compute the forces on the particles, nominally the force between each particle and every other particle is computed, a computational burden of O(n2).
Practically speaking, molecular dynamics programs reduce the O(n2) by cutting off pair interactions at some distance. However for many scientifically relevant molecular systems, the computational burden due to the particle pair interactions remains large. In order to reach scientifically relevant simulation times, parallel computers are required to compute particle pair interactions rapidly. See B. G. Fitch et al., “Blue Matter: Approaching the Limits of Concurrency for Classical Molecular Dynamics,” Proceedings of the ACM/IEEE SC 2006 Conference, Volume 11, Issue 17, November 2006, and B. G. Fitch et al., “Blue Matter, an Application Framework for Molecular Simulation on Blue Gene,” Journal of Parallel and Distributed Computing, vol. 63, pp. 759-773, July 2003, the disclosures of which are incorporated by reference herein.